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storage = {} storage['first'] = {} storage['middle'] = {} storage['last'] = {} The data structure storage is a dictionary with three keys: 'first', 'middle', and 'last'. Under each of these keys, you store another dictionary. In these subdictionaries, you ll use names (first, middle, or last) as keys, and insert lists of people as values. For example, to add me to this structure, you could do the following: >>> >>> >>> >>> me = 'Magnus Lie Hetland' storage['first']['Magnus'] = [me] storage['middle']['Lie'] = [me] storage['last']['Hetland'] = [me]

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We ll verify that the mapping works by creating unit tests for the mapping code. But let s first add some useful data to the books and publishers fixture files, which we ll use in later tests. Open test/fixtures/books.yml and add the following two books: pro_rails_ecommerce: id: 1 title: Pro Rails E-Commerce publisher_id: 1 isbn: 199-199-199-1 published_at: <%= Time.now.strftime("%Y-%m-%d") %> pro_rails_ecommerce_2: id: 2 title: Pro Rails E-Commerce 2nd Edition publisher_id: 1 isbn: 199-199-199-2 published_at: <%= Time.now.strftime("%Y-%m-%d") %> Note that the publisher_id column has been added to the fixture. This is a reference to a row in the database, which is inserted by the publishers.yml fixture file. Currently, no publisher has an id equal to 1, so you ll need to add the data to the publishers fixture file to complete the mapping.

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if (is_array($orders) && count($orders) > 0) { // output file header $csvFile = "!TRNS\t" . "TRNSID\t" . "TRNSTYPE\t" . "DATE\t" . "ACCNT\t" . "NAME\t" . "AMOUNT\t" . "ADDR1\t" . "ADDR2\t" . "ADDR3\t" . "ADDR4\t" . "ADDR5\t" . "SADDR1\t" . "SADDR2\t" . "SADDR3\t" . "SADDR4\t" . "SADDR5\t" . "PONUM\t" . "DOCNUM\t" . "SHIPDATE\t" . "TERMS\r\n"; $csvFile .= "!SPL\t" . "SPLID\t" . "TRNSTYPE\t" . "ACCNT\t" . "QNTY\t" . "PRICE\t" . "AMOUNT\t" . "INVITEM\t" . "MEMO\r\n"; $csvFile .= "!ENDTRNS\r\n"; // loop through the orders foreach ($orders as $orderInfo) { // this will store all the data before creating the CSV $orderInfoShipping = ''; $orderInfoBilling = ''; $orderInfoItems = array(); $salesCompletedDate = ''; $detailedInfo = array(); $orderId = (isset($orderInfo['order_increment_id']) $orderInfo['order_increment_id'] : ''); // // // if ======================================= STEP 2: extract more info (sales_order.info) ======================================= ($orderId)

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Under each key, you store a list of people. In this case, the lists contain only me. Now, if you want a list of all the people registered who have the middle name Lie, you could do the following: >>> storage['middle']['Lie'] ['Magnus Lie Hetland'] As you can see, adding people to this structure is a bit tedious, especially when you get more people with the same first, middle, or last names, because then you have to extend the list that is already stored under that name. Let s add my sister, for example, and let s assume you don t know what is already stored in the database: >>> my_sister = 'Anne Lie Hetland' >>> storage['first'].setdefault('Anne', []).append(my_sister) >>> storage['middle'].setdefault('Lie', []).append(my_sister) >>> storage['last'].setdefault('Hetland', []).append(my_sister) >>> storage['first']['Anne'] ['Anne Lie Hetland'] >>> storage['middle']['Lie'] ['Magnus Lie Hetland', 'Anne Lie Hetland'] Imagine writing a large program filled with updates like this it would quickly become quite unwieldy. The point of abstraction is to hide all the gory details of the updates, and you can do that with functions. Let s first make a function to initialize a data structure: def init(data): data['first'] = {} data['middle'] = {} data['last'] = {} In the preceding code, I ve simply moved the initialization statements inside a function. You can use it like this:

Tip You can write ERB in fixtures in the same way as in views. This allows you to create dynamic fixtures, as demonstrated in the books.yml fixture file, where Time.now is used to generate the published_at value. Although dynamic fixtures are useful in some situations, they should generally be avoided as they make tests more complex and less predictable.

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